AUTHOR=Li Mingli , Li Xiaojing , Das Tushar Kanti , Deng Wei , Li Yinfei , Zhao Liansheng , Ma Xiaohong , Wang Yingcheng , Yu Hua , Meng Yajing , Wang Qiang , Palaniyappan Lena , Li Tao 

TITLE=Prognostic Utility of Multivariate Morphometry in Schizophrenia

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2019.00245

DOI=10.3389/fpsyt.2019.00245

ISSN=1664-0640

ABSTRACT=Background: To explore whether multivariate morphometry could be used to predict the prognosis of schizophrenia.
Method: 62 first-episode, drug-naive patients with schizophrenia underwent brain magnetic resonance imaging scans at baseline (T0) and rescanned after 1-year follow-up (T1). Positive and Negative Syndrome Scale (PANSS) was used to assess their clinical manifestations. The source based morphometry (SBM) performed to analyze the gray matter volume (GMV), the contrasts of paired T tests for loading coefficients of GMV were constructed to test the components and show differences between two time points. The reduction rate in PANSS scores between at baseline and after 1-year was expressed as a ratio of the scores at baseline - adjusted change scores for positive symptoms (ADJpos), negative symptoms (ADJne) and disorganization symptoms (ADJdisorg). Multiple regression analysis (MRA) was conducted to predict ADJpos /ADJne / ADJdisorg of using the loading coefficients of components (showing T0/T1 difference) at baseline and 1-year with age and antipsychotic category as covariates, separately. MRA also was used to predict GMV at T1 of using the severity scores of PANSS at baseline and ADJpos /ADJne / ADJdisorg and antipsychotic dosage. 
Results: 30 spatial components of gray matter were extracted by SBM, of them, loading coefficients of anterior cingulate cortex (ACC), insular & inferior frontal gyrus (IFG), superior temporal gyrus (STG), middle temporal gyrus (MTG) and dorsal lateral prefrontal cortex (DLPFC) reduced with time in patients. Specially, the lower volume of insula & IFG at baseline and at 1-year related to poor improvement in positive and disorganization symptoms. The lower GMV of MTG and STG at baseline related to the higher severity of positive and disorganization symptoms in patients at 1-year. None of the symptom severity scores (positive, negative or disorganization) at baseline can predict the gray matter volume at 1-year.
Conclusions: The baseline deficits in insular & IFG, STG and MTG are predictive of the course of illness. If judiciously combined with other available predictors of prognosis, these morphometric measures can improve our ability to predict prognosis in schizophrenia.